Automatically Distributing Eulerian and Hybrid Fluid Simulations in the Cloud

Omid Mashayekhi, Chinmayee Shah, Hang Qu, Andrew Lim, Philip Levis Distributing a simulation across many machines can drastically speed up computations and increase detail. The computing cloud provides tremendous computing resources, but weak service guarantees force programs to manage significant system complexity: nodes, networks, and storage occasionally perform poorly or fail. We describe Nimbus, a […]

FEPR: Fast Energy Projection for Real-Time Simulation of Deformable Objects

Dimitar Dinev, Tiantian Liu, Jing Li, Bernhard Thomaszewski, Ladislav Kavan We propose a novel projection scheme that corrects energy fluctuations in simulations of deformable objects, thereby removing unwanted numerical dissipation and numerical “explosions”. The key idea of our method is to first take a step using a conventional integrator, then project the result back to […]

Anderson Acceleration for Geometry Optimization and Physics Simulation

Yue Peng, Bailin Deng, Juyong Zhang, Fanyu Geng, Wenjie Qin, Ligang liu Many computer graphics problems require computing geometric shapes subject to certain constraints. This often results in non-linear and non-convex optimization problems with globally coupled variables, which pose great challenge for interactive applications. Local-global solvers developed in recent years can quickly compute an approximate […]

An Advection-Reflection Solver for Detail-Preserving Fluid Simulation

Jonas Zehnder, Rahul Narain, Bernhard Thomaszewski Advection-projection methods for fluid animation are widely appreciated for their stability and efficiency. However, the projection step dissipates energy from the system, leading to artificial viscosity and suppression of small-scale details. We propose an alternative approach for detail-preserving fluid animation that is surprisingly simple and effective. We replace the […]

Projective Skinning

Martin Komaritzan, Mario Botsch We present a novel approach for physics-based character skinning. While maintaining real-time performance it overcomes the well-known artifacts of commonly used geometric skinning approaches, it enables dynamic effects, and it resolves local self-collisions. Our method is based on a two-layer model consisting of rigid bones and an elastic soft tissue layer. […]

Interactive Two-Way Shape Design of Elastic Bodies

Rajaditya Mukherjee, Longhua Wu, Huamin Wang We present a novel system for interactive elastic shape design in both forward and inverse fashions. Using this system, the user can choose to edit the rest shape or the quasistatic shape of an elastic solid, and obtain the other shape that matches under the quasistatic equilibrium condition at […]

Learning Nonlinear Soft-Tissue Dynamics for Interactive Avatars

Dan Casas, Miguel Otaduy We present a novel method to enrich existing vertex-based human body models by adding soft-tissue dynamics. Our model learns to predict per-vertex 3D offsets, referred to as dynamic blendshapes, that reproduce nonlinear mesh deformation effects as a function of pose information. This enables the synthesis of realistic 3D mesh animations, including […]

Comparison of Mixed Linear Complementarity Problem Solvers for Multibody Simulations with Contact

Andreas Enzenhofer, Sheldon Andrews, Marek Teichmann, Jozsef Kövecses The trade-off between accuracy and computational performance is one of the central conflicts in real-time multibody simulations, much of which can be attributed to the method used to solve the constrained multibody equations. This paper examines four mixed linear complementarity problem (MLCP) algorithms when they are applied […]

A Material Point Method for Thin Shells with Frictional Contact

Qi Guo, Xuchen Han, Chuyuan Fu, Theodore Gast, Rasmus Tamstorf, Joseph Teran We present a novel method for simulation of thin shells with frictional contact using a combination of the Material Point Method (MPM) and subdivision finite elements. The shell kinematics are assumed to follow a continuum shell model which is decomposed into a Kirchhoff-Love […]

Fluid Directed Rigid Body Control Using Deep Reinforcement Learning

Yunsheng Tian, Pingchuan Ma, Zherong Pan, Bo Ren, and Dinesh Manocha We present a learning-based method to control a coupled 2D system involving both fluid and rigid bodies. Our approach is used to modify the fluid/rigid simulator’s behavior by applying control forces only at the simulation domain boundaries. The rest of the domain, corresponding to […]